Traditional information retrieval (IR) techniques typically rely on vocabulary term matching when searching through documents to identify documents for a response. Specifically, these IR techniques typically sort through large numbers of documents (a “knowledge base”) to identify those documents having vocabulary words and/or phrases that match a user's typed input. As a result, documents that are potentially valuable to the user, and relevant to their input, but that do not happen to have matching vocabulary words and/or phrases often are neither retrieved nor returned to the user. These are referred to as “missed” results. Conversely, documents that are not of value to the user, but that happen to have matching vocabulary words and/or phrases, are often retrieved and/or returned to the user. These are “false alarm” results. One aspect of an IR system is to reduce both the number of misses and the number of false alarms.